Asia Pacific’s’ GDP stands to gain an extra US$387 billion by 2021 and grow by extra 1.0% annually if the region’s manufacturing sector embraces digital transformation, according to the new figures released by Microsoft today.
The results for manufacturing are outlined in the Study, “Unlocking the Economic Impact of Digital Transformation in Asia Pacific”, which was produced by Microsoft in partnership with IDC Asia/Pacific. It was based on the survey of 615 business leaders from the manufacturing sector across 15 markets in the region.
“The Study finds that escalating costs of operations are a number one concern among C-level executives within the sector. At the same time, they are increasingly aware of the need to develop new business models to grow the business to counter the rise of growing number of competitors in markets,” said Victor Lim, Vice President IDC Asia/Pacific.
“Embracing digital transformation is a critical imperative for manufacturers,” adds Lim. “Those organizations that had already embarked on their digital transformation journeys gained improvements in the range of 13% to 17% the last year. They will see at least 40% improvements in three years, with customer advocacy registering the highest improvement rate.”
The Study identifies the top three benefits of digital transformation that have a direct impact to bottom line performance:
Improvement in productivity
Improvement in profit margins
However, these businesses are also seeing long-term benefits when they embrace digital transformation. Increased revenue from new products and services and improved customer advocacy rounded up the top five benefits tracked from digital transformation.
Scott Hunter, Regional Business Lead, Manufacturing, Microsoft Asia said: “Looking ahead, digital transformation in Asia means moving the focus from process automation, optimization and productivity improvement efforts into developing new business models to stay competitive”.
Data is Key to Unlock Digital Transformation Potential
The Study finds that manufacturing organizations realize the importance of data today. In fact, 44% of respondents pointed out one of their key performance indicators (KPIs) used to measure digital transformation today is tracking how data is being used as a capital asset.
“It is no surprise that businesses are still focused on tracking process effectiveness as the manufacturing sector is one that relies heavily on time-to-market strategies for first mover advantage. However, as manufacturing organizations realize the value of data in the long term, they are likely to unlock the potential of digital transformation in helping them create new business models,” said Hunter.
Manufacturing organizations are going to invest in cloud and big data analytics, followed by AI, Cognitive and Robotics and Internet of Things solutions this year. In fact, by 2019, IDC predicts that 40% of digital transformation initiatives will be supported by Artificial Intelligence/ Cognitive capabilitie providing timely, critical insights for new operating and monetization models in Asia Pacific (excluding Japan).
Manufacturing Organizations Need to Overcome Skills, Culture and Cybersecurity Barriers
The Study also identified the key traits of Manufacturing Leaders (30) against other Leaders (73):
Manufacturing Leaders are more likely to have a key executive leading their Digital Transformation efforts.
However, leaders in the manufacturing sector are less likely to have an allocated budget set aside for Digital Transformation as part of their existing Profit & Loss statement.
In addition, manufacturing Leaders are likely more siloed in their organizational behavior, whereby there are lesser agility and collaboration across teams in the change cycle.
When it comes to key challenges identified in embarking digital transformation initiatives today, the top three factors included:
Lack of skills and resources
Cybersecurity and growing threats
Siloed and resistant culture
“Digital transformation should be viewed as a team sport, not an independent business operation. Manufacturing organizations need to address culture and skills challenges through developing a digital culture and address organizational shifts required for a change to happen,” added Hunter. “First and foremost, organizations need to address the skills gap within the industry. In fact, respondents highlighted that they expect 85% of jobs within the sector to be transformed in the next three years.”
Developing New Business Models in the Digital Age
“Ultimately, manufacturing organizations need to move from process automation to a holistic, enterprise-wide transformation in order to attain competitive advantages,” shared Lim. “There are three approaches to this – first, the organization needs to develop a digital culture, followed by having a structured approach to the use of data, which is supported by introducing new technologies into the workstreams. Ultimately, a successfully transformed manufacturer will see the development of a digital supply chain whereby there is a fully automated feedback loop within the ecosystem to allow for full control, coordination and visibility across all parties Additionally, working with a trusted technology partner is crucial for the success of organizations in their digital transformation journeys.”
The Study recommends organizations to adopt a three-step data strategy to become a digital transformation leader:
Collection of Data: Organizations need to have in place a data strategy to manage structured and unstructured data within the workstreams. By investing in big data analytics and IoT solutions, manufacturers are better able to collect and sort data in a cohesive manner.
Optimisation of Existing Products and Services through Data: Leveraging data, organizations in the manufacturing sector can seek to optimize their processes, supply chain and ultimately deliver improvements to their existing product and services. Using big data analytics, machine learning and artificial intelligence, businesses are able to improve efficiencies through predictive analysis.
Creating New Business Models with Data: Ultimately, data should be used to create new value chains and services (i.e. predictive maintenance, 3D Modelling and Smart Operations).